From 9a565cd5d60770ca8d10c73b574ad637d6352458 Mon Sep 17 00:00:00 2001
From: Philipp Arras <parras@mpa-garching.mpg.de>
Date: Sun, 15 Aug 2021 17:28:42 +0200
Subject: [PATCH] 7/n
---
2_critical_filter_solution.py | 10 +++++-----
3_more_examples.py | 8 +++-----
teaser_critical_filter.py | 9 ++-------
3 files changed, 10 insertions(+), 17 deletions(-)
diff --git a/2_critical_filter_solution.py b/2_critical_filter_solution.py
index 0fe2001..8e78e3e 100644
--- a/2_critical_filter_solution.py
+++ b/2_critical_filter_solution.py
@@ -63,14 +63,14 @@ H = ift.StandardHamiltonian(likelihood, ic_sampling)
initial_mean = ift.MultiField.full(H.domain, 0.)
mean = initial_mean
-# Draw five samples and minimize KL, iterate 10 times
-for _ in range(3):
+# Draw five samples and minimize KL, iterate 5 times
+n_rounds = 5
+for ii in range(n_rounds):
KL = ift.MetricGaussianKL(mean, H, 5, True)
+ KL = ift.MetricGaussianKL(mean, H, 30 if ii == n_rounds-1 else 5, True)
KL, convergence = minimizer(KL)
mean = KL.position
-# Draw posterior samples and plot
-N_posterior_samples = 30
-KL = ift.MetricGaussianKL(mean, H, N_posterior_samples, True)
+# Plot posterior samples
plot_reconstruction_2d(data, ground_truth, KL, signal, R, signal.amplitude,
'2_criticalfilter')
diff --git a/3_more_examples.py b/3_more_examples.py
index b71980f..a82507b 100644
--- a/3_more_examples.py
+++ b/3_more_examples.py
@@ -73,12 +73,10 @@ for mode in [0, 1]:
H = ift.StandardHamiltonian(likelihood, ic_sampling)
initial_mean = ift.MultiField.full(H.domain, 0.)
mean = initial_mean
- N_samples = 5
- for _ in range(5):
+ n_rounds = 5
+ for ii in range(n_rounds):
# Draw new samples and minimize KL
- KL = ift.MetricGaussianKL(mean, H, N_samples, True)
+ KL = ift.MetricGaussianKL(mean, H, 30 if ii == n_rounds-1 else 5, True)
KL, convergence = minimizer(KL)
mean = KL.position
- N_posterior_samples = 30
- KL = ift.MetricGaussianKL(mean, H, N_posterior_samples, True)
h.plot_reconstruction_2d(data, ground_truth, KL, signal, R, A, name[mode])
diff --git a/teaser_critical_filter.py b/teaser_critical_filter.py
index a0cee0e..468caeb 100644
--- a/teaser_critical_filter.py
+++ b/teaser_critical_filter.py
@@ -78,18 +78,13 @@ mean = initial_mean
N_samples = 10
# Draw new samples to approximate the KL ten times
-for i in range(10):
+for _ in range(10):
# Draw new samples and minimize KL
KL = ift.MetricGaussianKL(mean, H, N_samples, True)
KL, convergence = minimizer(KL)
mean = KL.position
- # FIXME Minimize posterior samples (global)
-# Draw posterior samples and plotting
-N_posterior_samples = 10
-KL = ift.MetricGaussianKL(mean, H, N_posterior_samples, True)
-
-# Plot the reconstruction result
+# Plot posterior samples
ground_truth = ift.makeField(position_space, ground_truth)
posterior_samples = [correlated_field(KL.position+samp) for samp in KL.samples]
mean = 0.*posterior_samples[0]
--
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